Computing Efficient Solutions of Nonconvex Multi-Objective Problems Via Scalarization
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Date
2011
Authors
Kasimbeyli R.
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Publisher
Open Access Color
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Abstract
This paper presents a new method for scalarization of nonlinear multi-objective optimization problems. We introduce a special class of monotonically increasing sublinear scalarizing functions and show that the scalar optimization problem constructed by using these functions, enables to compute complete set of weakly efficient, efficient, and properly efficient solutions of multi-objective optimization problems without convexity and bound-edness conditions.
Description
11th WSEAS International Conference on Signal Processing, Computational Geometry and Artificial Vision, ISCGAV'11, 11th WSEAS International Conference on Systems Theory and Scientific Computation, ISTASC'11 -- 23 August 2011 through 25 August 2011 -- Florence -- 87580
Keywords
Cone separation theorem, Conic scalarization method, Multi-objective optimization, Proper efficiency, Sublinear scalarizing functions, Multi objective, Proper efficiency, Scalarization method, Separation theorem, Sublinear, Signal processing, System theory, Theorem proving, Multiobjective optimization
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Source
Recent Advances in Signal Processing, Computational Geometry and Systems Theory - ISCGAV'11, ISTASC'11
Volume
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Start Page
193
End Page
198
